torcheval.metrics.BLEUScore¶
- class torcheval.metrics.BLEUScore(*, n_gram: int, weights: Tensor | None = None, device: device | None = None)¶
Compute BLEU score (https://en.wikipedia.org/wiki/BLEU) given translations and references. Its functional version is
torcheval.metrics.functional.text.bleu.- Parameters:
n_gram – Maximum n-gram to use when computing BLEU score. Can be 1, 2, 3, or 4.
weights – Optional weight distribution of n-grams. Requires len(weights) = n_gram. If unspecified, will use uniform weights.
Examples
>>> import torch >>> from torcheval.metrics import BLEUScore >>> metric = BLEUScore(n_gram=4) >>> candidates = ["the squirrel is eating the nut", "the cat is on the mat"] >>> references = [["a squirrel is eating a nut", "the squirrel is eating a tasty nut"], ["there is a cat on the mat", "a cat is on the mat"]] >>> metric.update(candidates, references) >>> metric.compute() tensor(0.65341892) >>> candidates = ["i like ice cream and apple pie"] >>> references = [["i like apple pie with ice cream on top", "i like ice cream with my apple pie", "i enjoy my apple pie with ice cream"]] >>> metric.update(candidates, references) >>> metric.compute() tensor(0.56377503)
- __init__(*, n_gram: int, weights: Tensor | None = None, device: device | None = None) None¶
Initialize a metric object and its internal states.
Use
self._add_state()to initialize state variables of your metric class. The state variables should be eithertorch.Tensor, a list oftorch.Tensor, a dictionary withtorch.Tensoras values, or a deque oftorch.Tensor.
Methods
__init__(*, n_gram[, weights, device])Initialize a metric object and its internal states.
compute()Returns the running BLEUScore.
load_state_dict(state_dict[, strict])Loads metric state variables from state_dict.
merge_state(metrics)Merge the metric state with its counterparts from other metric instances.
reset()Reset the metric state variables to their default value.
state_dict()Save metric state variables in state_dict.
to(device, *args, **kwargs)Move tensors in metric state variables to device.
update(input, target)Update the metric state with new inputs.
Attributes
deviceThe last input device of
Metric.to().